Functionality of conventional mapping applications that are accessible by way of the Internet has substantially increased over time. For instance, the user can access a mapping application and be provided with an overhead view of one or more streets. Further, the user may provide an initial location (e.g., street address) and a destination and the mapping application can provide the user with detailed directions pertaining to traveling between the initial location and the destination.
Mapping applications have further developed such that an individual can view aerial images of a particular region. For instance, if a user enters a particular location (e.g., address, business name) the user can be provided with aerial images pertaining to such entered location. These images may then be subjected to a zooming function such that the user can be provided with a relatively close aerial view of the entered location. Furthermore, driving directions may be graphically laid on top of the aerial images, thus providing the user with some context with respect to a route to be traveled between the initial location and the destination.
Some mapping applications have further been adapted to include three-dimensional models of buildings in certain cities. Thus, a user can enter a location into the mapping application and be placed in a three-dimensional model pertaining to such location. The user may then navigate the three-dimensional model to be provided with context pertaining to the location. For example, if the user is planning to travel to Paris, France the user can provide the mapping application with the location of Paris, France and be provided with a three-dimensional representation of the city. The user may then navigate the representation and be provided with a first person perspective of one or more buildings, streets, etc. pertaining to the city of Paris. Thus, the user can “travel” through the city by way of the representation to obtain information pertaining to such city, such as the height of buildings, location of buildings in respect to one or more streets, etc.
Typically these three-dimensional models are generated first and thereafter are updated with aerial images which can be used to provide greater information pertaining to a building or buildings such as the look/texture of a building facade. Because these images are aerial images, however, the resolution of the images is less than desired. Moreover the captured aerial images may not be well-suited for adaption to a three-dimensional model.
Accordingly, it may be desirable to adapt a vehicle with one or more cameras to capture images of building facades in one or more cities as well as adapt the vehicle with various sensors to collect metadata pertaining to captured images. This data, for instance, may thereafter be used to automatically generate three-dimensional representations of a geographic region including one or more buildings, cities, etc. In an example, it may be desirable to determine velocity and/or location data pertaining to a particular captured image. Such metadata can be captured, for instance, by one or more sensors such as a GPS sensor, a velocity sensor, an accelerometer, etc. GPS receivers, however, may not provide sufficient accuracy for automatically generating a three-dimensional model, as a typical GPS receiver can have an error in the range of +/−5 meters for each sensed location output by the GPS receiver. Other sensors exist that are capable of providing highly accurate position, velocity and/or acceleration data. However, such sensors tend to be extraordinarily expensive (e.g., in the range of tens of thousands of dollars). On the other hand, low cost sensors tend to provide data with less than sufficient accuracy for automated generation of three-dimensional models.